Solutions Architect, AI and ML

As a Solutions Architect at NVIDIA, your primary responsibilities include engaging with customers to adopt GPU technologies, demonstrating AI/ML solutions in collaboration with Cloud Service Providers, building customized Proofs of Concept, and partnering with Sales Account Managers to identify business opportunities. You will also conduct customer meetings to discuss project roadmaps and technical strategies.

To become a Solutions Architect at NVIDIA, you should have a minimum of 3 years in Solutions Engineering or a similar role, with extensive experience in Deep Learning and Machine Learning. A BS/MS/PhD in a relevant engineering field is preferred. Familiarity with cloud environments like AWS, GCP, or Azure, along with programming skills, will elevate your candidacy.

NVIDIA is committed to the professional development of its Solutions Architects. With access to cutting-edge training, mentorship, and the opportunity to work with industry-leading technologies, you will continually enhance your skills. Networking at industry events and workshops also plays a key role in career advancement.

Solutions Architects at NVIDIA leverage a multitude of technologies, including NVIDIA’s AI software, deep learning frameworks like TensorFlow and PyTorch, and cloud platforms such as AWS, GCP, or Azure. Familiarity with DevOps/ML Ops tools like Docker and Kubernetes is also beneficial.

Yes, while most collaboration is conducted using conferencing tools, occasional travel is required for on-site visits with customers and participation in industry events, enhancing customer relationships and keeping you engaged with the AI community.

In your response, highlight specific projects where you've deployed solutions on cloud platforms like AWS, GCP, or Azure. Discuss challenges you faced and how you overcame them, demonstrating your technical understanding and hands-on experience.

Discuss your expertise in frameworks such as TensorFlow or PyTorch, detailing specific projects where you implemented these technologies. Be prepared to explain the impact of your work and how it addressed business needs.

Select a specific example where you identified the customer's core issue, devised a solution leveraging NVIDIA technology, and executed it effectively. Highlight any collaboration with other teams, emphasizing teamwork.

Emphasize your ability to simplify complex ideas by using relatable analogies and visual aids. Discuss examples where your communication skills enabled successful outcomes in customer meetings or presentations.

Share your strategies for continuous learning, such as attending workshops, engaging with online communities, participating in relevant certifications, and following industry thought leaders. Convey your passion for learning.

Talk about instances where you developed and delivered presentations, focusing on how you tailored your content to meet audience needs while effectively conveying technical solutions and features.

Discuss your approach to soliciting feedback from peers and customers, how you integrate it into your work processes, and the positive results that arose from making adjustments based on that feedback.

Detail any hands-on experience you have had with NVIDIA GPUs or SDKs, including specific projects where their capabilities significantly enhanced your solutions. Share what you've learned about leveraging these technologies.

Explain your time management strategies, such as using project management tools and techniques to keep tasks structured and focused, while being adaptable to shifts in priorities based on customer needs.

Express your enthusiasm for NVIDIA’s mission and dedication to innovation in AI and ML. Discuss how your skills and experiences align with the company's goals, showcasing your desire to contribute positively.